UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN

Department of Electrical and Computer Engineering

 

ECE 310: Digital Signal Processing

http://courses.ece.uiuc.edu/ece310

Fall 2016


       

 

Administrative Information

Assoicated Lab Course:

ECE 311: Digital Signal Processing Lab

 

Lecture Times:

Lecture

G

10:00 AM - 10:50 PM

Mon./Wed./Fri.

3017 ECEB

Prof. Stephen Levinson

Lecture

E

3:00 PM - 3:50 PM

Mon./Wed./Fri.

3017 ECEB

Prof. Yoram Bresler

 

Instructors:

Prof. Yoram Bresler

Prof. Stephen Levinson

Office: 112 CSL

Office: ECE3048

Email: ybresler@illinois.edu

Email: selevins@illinois.edu

* Office Hours by appointment

* Professors Bresler and Levinson will alternate teaching both sections throughout the semester.

 

Teaching Assistants:

Ali Abavisani: aliabavi@illinois.edu           Yuhui Lai: lai35@illinois.edu                 Wyatt McAllister: wmcalli2@illinois.edu

 

The Teaching Assistants for the course will hold recitations, in which they will solve problems on the board and/or review course material, as well as office hours, during which they will answer specific questions from students.

TA Office Hours:   

Tuesday 5-6pm TA: Wyatt McAllister (ECEB 3020)

Wednesday 5-6pm TA: Ali Abavisani (ECEB 3020)

Thursday 5-6pm TA: Yuhui Lai (ECEB 2013)

Recitation (ECEB3013): Tuesday 6-7pm

 

Integrity:

This course will operate under the following honor code: Students may collaborate on working through homework assignments, but each student must turn in his or her own work that has been worked out independently of any other student. Looking for solutions from prior year handouts or copying of other student's work is considered cheating and will not be permitted. All exams and quizzes are to be worked out independently without any aid from any person or device. By enrolling in this course and submitting HW assignments, quizzes, and exams for grading, each student implicitly accepts this honor code.

 

Course Objectives:

Upon completion of this course, you should be able to:

Syllabus:

#

Week

Reading

Concept matrix

Quiz

Homework set Due

1

8/22 - 8/26  

Ch 1

AppxA

AppxD

DSP overview;

Continuous-time (CT) and discrete-time (DT) signals;

Complex numbers;

Impulses

 

 

2

8/29 - 9/2    

Ch 2.1, 2.2, 2.3

2.4, 2.5

Fourier transform (FT);

Discrete-time Fourier transform (DTFT); DTFT of sinusoidal signals.

 

 

H1

 

   9/5

 

Labor Day

   

3

9/6 - 9/9

Ch 2.4, 2.5

Discrete-time Fourier transform (DTFT); Discrete Fourier transform (DFT)

 Q1 Wed 9/7       

H2

4

9/12 - 9/16

Ch  2.5- 2.6

Ch  3.1-3.2

 

Discrete Fourier transform (DFT); DFT spectral analysis;

Sampling;

Ideal A/D (analog-to-digital) converter

 

H3

5

9/19 - 9/23

Notes Ch 3.3-3.9

Opponheim-Shafer: 2.2-2.4

Proakis-Manolakis: 2.2-2.3

 

 

Linear and shift invariant systems;

Convolution;

Impulse response

 Q2 Wed 9/21

8:15-9:15 pm

 H4

6

9/26 - 9/30

Notes: Ch 4.1-4.5, 4.8, 4.10, 4.12-4.14

 

Opponheim-Shafer: 2.5, 3.1, 3.3.2, 3.4

 

Proakis-Manolakis: 2.4, 3.1-3.3, 3.4.3

Unilateral z-transform (for right-sided signals);

Poles and zeros;

Inverse z-transform

Difference equations;Solution using the z-transform.

Transfer Function;

System block diagrams;

Convolution via z-transform;

System analysis;

BIBO stability

 

H5

7

10/3 - 10/7

Lecture notes: Ch 5.1, Ch 5.2

Opponheim-Shafer: 2.6, 2.7, 2.9, 5.1

Proakis-Manolakis: 4.2.3, 4.2.6, 5.1-5.2

Frequency representation of signals;

Frequency response of systems;

Magnitude and phase response

 Q3 Wed 10/5

H6

8

10/10 - 10/14

Notes: Ch 6.3-6.4, Ch. 11(old notes)

Opponheim-Shafer: 6.1, 7.2

Proakis-Manolakis: 2.5, 9.1, 10.1.2, 10.2.2

Digital filter structures;

FIR and IIR filters;

FIR filter design - the windowing method

 

    H7

9

10/17 - 10/21

Ch 9

Analog frequency response of a digital processor;

Applications of DSP systems

 Q4 Wed 10/19

    H8

10

10/24 - 10/28

Ch 13

Downsampling and upsampling;

Oversampling A/D and D/A;

Digital interpolation

 

    H9

11

10/31 - 11/4

Ch 14

Fast Fourier Transform (FFT);

Fast Convolution

 Q5

Tuesday 11/1

5:30-6:30pm

    H10

12

11/7 - 11/11

Introduction to Vector-Space Signal Processing: Part 1

Signal as vectors;

Signal representation and transformation;

Linear systems as matrices;

 

    H11

13

11/14 - 11/18

Introduction to Vector-Space Signal Processing: Part 2

LMS Demo in MATLAB

Singular Value Decomposition

Linear regression and least-squares filtering

SVD and principal component analysis

 Q6 Wed 11/16

    H12

14

11/21 - 11/25

 

Thanksgiving break

 

 

15

11/28 - 12/2

Ch 12

IIR Filters: butterworth, Chebychev, Elliptical
Applications of digital filtering;

 

    H13

16

12/5 - 12/7

Ch 15

Review;

Applications